Submission: tacmagic - PET Analysis in R

[eebrown]

Submitting Author: Eric Brown (@eebrown)
Repository: https://github.com/eebrown/PET
Version submitted: 0.1.9
Editor: Melina Vidoni (@melvidoni)
Reviewer 1: Jon Clayden (@jonclayden)
Reviewer 2: Brandon Hurr (@bhive01)
Archive: TBD
Version accepted: TBD

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• Paste the full DESCRIPTION file inside a code block below:

Package: tacmagic
Type: Package
Title: tacmagic: PET Analysis in R
Version: 0.1.9
Authors@R: c(person("Eric", "Brown", 
                    role = c("aut", "cre"),
                    email = "eb@ericebrown.com",
                    comment = c(ORCID = "0000-0002-1575-2606")),
             person("Ariel", "Graff-Guerrero",
                    role = c("dgs")))
Description: To faciliate analysis of positron emission tomography (PET) time
    activity curve (TAC) data, and to encourage open science and replicability,
    this package supports data loading and analysis of multiple TAC file 
    formats. Functions are available to analyze loaded tac data for individual 
    participants or in batches. Major functionality includes weighted TAC 
    merging by region of interest (ROI), calculating models including SUVR and
    DVR, basic plotting functions and calculation of cut-off values. Please see
    the walkthrough vignette for a detailed overview of tacmagic functions.
Depends: R (>= 3.4)
License: GPL-3
URL: https://github.com/eebrown/PET
BugReports: https://github.com/eebrown/PET/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: 
    graphics, 
    grDevices, 
    pracma, 
    utils,
    R.matlab
Suggests:
    testthat,
    knitr,
    rmarkdown,
    covr
VignetteBuilder: knitr

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • data retrieval
  • data extraction
  • database access
  • data munging
  • data deposition
  • reproducibility
  • geospatial data
  • text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

Please see the presubmission inquiry as this package was deemed in scope.(#277)

This packages supports loading positron emission tomography (PET) time-activity curves (TACs) from several different major formats, to allow a common subsequent analysis pipeline within R ("data extraction"). There are functions to support merging of regional time-activity curves, an often important analysis step ("data munging"). Additional analysis is available in the package, which virtue of being open source promotes open science reproducibility.

• Who is the target audience and what are scientific applications of this package?

Scientists working with PET data needing to analyze TAC data in R can take advantage of the loading (including batch loading) functions and basic plotting. Those who need basic non-invasive models can take advantage of the implemented models. We will invite contributors to extend the package in its support for file formats and models.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

There do not appear to be packages that offer the loading and merging functions. There are packages that have some PET models implemented but not full overlap.

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

Issue #277 - @sckott

Technical checks

Confirm each of the following by checking the box. This package:

• does not violate the Terms of Service of any service it interacts with.
• has a CRAN and OSI accepted license.
• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions.
• contains a vignette with examples of its essential functions and uses.
• has a test suite.
• has continuous integration, including reporting of test coverage using services such as Travis CI, Coveralls and/or CodeCov.

Publication options

• Do you intend for this package to go on CRAN?
• Do you wish to automatically submit to the Journal of Open Source Software? If so:

JOSS Options

• The package has an obvious research application according to JOSS's definition.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:
  • (Do not submit your package separately to JOSS)

• Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

MEE Options

• The package is novel and will be of interest to the broad readership of the journal.
• The manuscript describing the package is no longer than 3000 words.
• You intend to archive the code for the package in a long-term repository which meets the requirements of the journal (see MEE's Policy on Publishing Code)
• (Scope: Do consider MEE's Aims and Scope for your manuscript. We make no guarantee that your manuscript will be within MEE scope.)
• (Although not required, we strongly recommend having a full manuscript prepared when you submit here.)
• (Please do not submit your package separately to Methods in Ecology and Evolution)

Code of conduct

• I agree to abide by ROpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

[sckott]

thanks for your submission @eebrown - @melvidoni has been assigned as editor

[melvidoni]

Editor checks:

• Fit: The package meets criteria for fit and overlap
• Automated tests: Package has a testing suite and is tested via Travis-CI or another CI service.
• License: The package has a CRAN or OSI accepted license
• Repository: The repository link resolves correctly
• Archive (JOSS only, may be post-review): The repository DOI resolves correctly
• Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

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Editor comments

Thank you for your submission @eebrown! The output from goodpractice is perfect. I will start looking for reviewers.

Preparing: covr
Preparing: cyclocomp
Preparing: description
Preparing: lintr
Preparing: namespace
Preparing: rcmdcheck

♥ Mhm! Wonderful package! Keep up the majestic work!

Please add the badge to your repo. Edit the code below with your issue ID:

[![](https://badges.ropensci.org/<issue_id>_status.svg)](https://github.com/ropensci/software-review/issues/<issue_id>)

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Reviewers: Jon Clayden (@jonclayden) & Brandon Hurr (@bhive01)
Due date: February 22nd

[eebrown]

Thank you very much @melvidoni. I've added the badge.

[melvidoni]

Reviewers have been assigned: Jon Clayden (@jonclayden) & Brandon Hurr (@bhive01)
The due date for the reviews is February 22nd.